| Summary: | 碩士 === 中原大學 === 電機工程研究所 === 105 === The photovoltaic panels have plural operational regions for power generation under partial shading conditions, such that the traditional maximum power point tracking(MPPT) methods will lead to local maximum power generation. To obtain the global maximum power generation, this thesis proposes a hybrid method by combining Shuffled Frog Leaping Algorithm(SFLA) and Perturb and Observe(P&O) algorithm. A grid-tied PV power generation system is taken as the application, where a boost converter and a full-bridge inverter are used to transfer the PV power for grid-tied systems. Moreover, the neural network based on fractional-order PI current control is used for the current regulation of the full-bridge inverter. Finally, numerical simulation and experimental results show the expected performance of the global maximum power point tracking under partial shading conditions.
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